Goal of the analysis

Research question: How does the relationship between population density and temperature vary across different land use types around Netherlands?

Data

Scope

Figure 1: Districts in the Netherlands

Outcome variable: Temperature

Figure 2: Average Temperature Across the Netherlands

Control variable: Population density

Summary Statistics

Table 1: Summary statistics

Land Use Type	Sample Size	Mean Temperature (°C)	SD Temperature (°C)	Mean Population	Median Population	Correlation temperature ~ population
Forests	1,644	11.16	0.29	2.57	1.49	0.08
Urban fabric	1,555	11.21	0.27	7.68	5.91	0.11
Industrial, commercial and transport units	1,109	11.22	0.24	6.50	4.65	0.02
Artificial, non-agricultural vegetated areas	1,036	11.19	0.26	7.71	4.92	0.03
Heterogeneous agricultural areas	888	11.23	0.27	2.82	1.87	0.14
Arable land	802	11.23	0.26	2.88	1.81	0.10
Pastures	736	11.22	0.27	3.57	2.19	0.05
Scrub and/or herbaceous vegetation associations	603	11.15	0.31	2.16	1.15	0.11
Inland waters	420	11.17	0.28	3.72	2.09	0.18
Inland wetlands	278	11.15	0.28	2.46	1.19	0.05
Mine, dump and construction sites	258	11.22	0.25	5.07	2.74	0.00
Permanent crops	75	11.31	0.14	2.21	1.63	-0.13
Maritime wetlands	74	11.37	0.26	1.12	0.57	0.30
Open spaces with little or no vegetation	58	11.26	0.24	2.13	0.81	0.20
Marine waters	5	11.17	0.35	2.47	2.62	-0.69
Source: Data from Netherlands 2019: Temperature (CHELSA), Population (WorldPop), Land Use (Corine)

Figure 3: Correlation between Temperature and Population by Land Use Type across the Netherlands

Regression models

Table 2: Regression Results

Variable	Model 1: Population Only¹	Model 2: Land Use Only²	Model 3: Full Model³
Outcome Variable: Temperature in °C
Intercept	11.158*** (0.007)	11.206*** (0.004)	11.154*** (0.012)
Log(Population + 1)	0.031*** (0.004)		0.027*** (0.006)
Log(Pop) × Land Use: Agricultural areas			0.026* (0.012)
Log(Pop) × Land Use: Forest and semi natural areas			0.041** (0.014)
Log(Pop) × Land Use: Water bodies			0.076** (0.029)
Log(Pop) × Land Use: Wetlands			-0.007 (0.034)
landuseAgricultural areas		0.022** (0.007)	0.009 (0.019)
landuseForest and semi natural areas		-0.045*** (0.007)	-0.046* (0.020)
landuseWater bodies		-0.035* (0.014)	-0.125** (0.043)
landuseWetlands		-0.007 (0.015)	0.021 (0.040)
Standard errors in parentheses. Significance: † p < 0.1, * p < 0.05, p < 0.01, * p < 0.001
¹ n = 7,486 \| R² = 0.007 \| Adj. R² = 0.007 \| RMSE = 0.262
² n = 9,528 \| R² = 0.008 \| Adj. R² = 0.008 \| RMSE = 0.271
³ n = 7,486 \| R² = 0.016 \| Adj. R² = 0.014 \| RMSE = 0.261

The analysis of temperature patterns across the Netherlands reveal that areas with higher population density consistently experience elevated temperatures. Model 1 demonstrates that a logarithmic increase in population density corresponds to a 0.031°C increase in temperature.

If we take a look at the Model 2, where we differenciate between different land use types, we can see that agricultural areas show slightly elevated temperatures, while forested and semi-natural areas provide significant cooling effects, reducing temperatures by approximately 0.045°C. Water bodies also contribute to local cooling, though to a lesser extent than forests. Wetlands show no significant temperature deviation from the baseline, suggesting they maintain relatively neutral thermal characteristics.

The most interesting findings emerge from the interaction between population density and land use type in the full model. Water bodies demonstrate the strongest interaction effect, where populated areas near water experience amplified warming despite water’s typical cooling properties. Similarly, forested areas with higher population density show increased temperatures, suggesting that human development can override the natural cooling benefits of vegetation. Agricultural areas exhibit a weaker but still significant interaction, while wetlands appear to buffer against population-related temperature increases, showing no significant interaction effect.

These results indicate that land use type serves as an important moderator in the population-temperature relationship. While the overall explanatory power remains modest, with R2 values between 0.007 and 0.016, the findings demonstrate that the urban heat island effect varies significantly depending on the surrounding land use context. This suggests that urban planning strategies should consider not just population density but also the thermal characteristics of different land use types when addressing local climate impacts.